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Energy Strategy Reviews

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Economic appraisal and scoping of geothermal energy extraction projectsusing depleted hydrocarbon wells

Dan Westphala,b, Ruud Weijermarsa,∗

aHarold Vance Department of Petroleum Engineering, Texas A&M University, 3116 TAMU College Station, TX, 77843-3116, USAbARM Energy, 20329 State Highway 249 Floor 4 Houston, TX, 77070, USA

A R T I C L E I N F O

Keywords:GeothermalEconomicsShaleGreenLow-temperature

A B S T R A C T

This study offers a first step in examining a potential solution for what to do with the ever-increasing number ofhorizontal shale wells in the United States (and lately, Argentina and China), as they come to the end of theireconomic life. A comprehensive decision-making tool was developed for scoping assessments based on thetechnical and economic appraisal of abandoned hydrocarbon wells repurposed into enhanced geothermal sys-tems. We specifically target near end-of-life oil and gas wells, re-commissioned to extract geothermal energy asopposed to hydrocarbons, because these potential geothermal resources are prevalent near a handful of major USpopulation and energy demand centers, including Pittsburgh, Houston, Denver, Dallas, Oklahoma City and SanAntonio. This study addresses some of the technical challenges associated with such projects. However, the mainfocus is on (1) the probabilistic evaluation of the economic net present value, and (2) specific solutions forpossible commercial deal structures required for negotiation and project implementation. The backdrop for thetest case in this study is the new Texas A&M RELLIS Campus being constructed in College Station, Texas. Asuccessful commercial model for the use of abandoned oil and gas wells to extract low and medium temperaturegeothermal resources could spur further development and a pilot study is proposed for this green source ofenergy. Our estimations suggest a net present value of $1.2 billion could be unlocked in the US alone, throughthe repurposing of wells, previously used for hydrocarbon extraction only.

1. Introduction

First commercial use of geothermal energy started in the western USalmost 60 years ago, when the Pacific Gas and Electric Company in-stalled a 12MW power generation unit in the Geysers Project, SonomaCounty, California [5]. Currently, the US is the global leader in geo-thermal power capacity (3567MW in 2016) and has almost 80 geo-thermal projects in various phases of development [6]. Nonetheless,after almost 60 years of development, geothermal power only accountsfor< 0.5% of net power generation for US utilities [7]. Conversion ofgeothermal heat into commercial power supply projects has been lim-ited to the western US, where shallow crustal temperatures are rela-tively high, especially in so-called hydrothermal zones (Fig. 1). Thepresent study aims to expand the reach of economic geothermal energyutilization in US regions where geothermal resources are still under-utilized, by providing a scoping template for low-temperature (LT)geothermal resource extraction projects using depleted oil and gaswells. Typically, LT geothermal resources do not provide enough heatfor the generation of electrical power (see Section 2.1), however other

direct-use solutions may be feasible. In LT regions, higher temperaturesoccur at greater depths, which would raise drilling cost, which is pre-emptive for developing such LT geothermal resources in any primaryproject. The repurposing of abandoned oil and gas wells would considerthe drilling cost as a sunk cost after depreciation over the life of theoriginal hydrocarbon extraction project, providing scope for secondarywell life for geothermal energy extraction.

The opportunity set for this type of refurbishing project is relativelyvast, given the location of tens of thousands of aging and abandonedwells in unconventional shale plays throughout the US. Over 100,000oil and gas wells have been drilled and are still active as of today [1].However, these wells typically have a limited life-span (< 40 years)and ultimately will need to be plugged and abandoned (P&A) once theireconomic life has come to an end. The P&A cost currently amounts to$50 k per well [2]. The option to repurpose the depleted hydrocarbonwells to generate a new cash-flow stream would push the P&A cost outfurther into the future while generating extra revenue, which offers anattractive alternative to P&A when further hydrocarbon extraction be-comes economically unfeasible.

https://doi.org/10.1016/j.esr.2018.10.008Received 12 December 2017; Received in revised form 11 October 2018; Accepted 23 October 2018

∗ Corresponding author.E-mail address: r.weijermars@tamu.edu (R. Weijermars).

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One of the first shale plays to see extensive horizontal well devel-opment was the Barnett Shale located just outside of Dallas. Subsequentdevelopment of the Austin Chalk/Woodbine (Houston), Eagle Ford (SanAntonio), Marcellus (Pittsburgh), Woodford (Oklahoma City) andNiobrara (Denver) have created a situation with oil and gas develop-ment directly adjacent to major population centers [3]. A prime ex-ample is the development of some 90 gas wells by Chesapeake a decadeago at the Dallas-Fort Worth International Airport [4], which was fol-lowed by a similar deal for the development of hydrocarbon wells atPittsburg Airport. Fig. 2 shows the major population centers, well lo-cations, and well density of various major US shale plays. Most of theseregions have wells reaching beyond 8000 ft vertical depth with sig-nificant horizontal sections up to another 8000 ft long, commonly withenhanced access to the reservoir due to hydraulic fracture treatment.

The decision-making model developed in this study is based on ascoping assessment of the technical and economic potential of the tar-geted wells when developed into an enhanced geothermal system (EGS)for space conditioning. Installment of injection and production pumpsfor brine circulation to retrieve heat from the reservoir would be ne-cessary, as well as investment in the surface space-conditioning in-stallations. A comprehensive scoping assessment of such projects hasnot been attempted before. Our study aims to fill this gap in con-temporary knowledge and provides a useful tool for further studies. Apilot study for refurbishing abandoned hydrocarbon wells is underwayat the new Texas A&M RELLIS Campus [39], which provided the field

specification used in our assessment tool.

2. Geothermal energy use from oil and gas wells

2.1. Pros and cons of reusing oil and gas wells

The idea to utilize oil and gas wells for geothermal energy extrac-tion has been raised in numerous prior studies [12–20]. The economicthreshold for commercial geothermal projects would be lowered be-cause drilling the wells takes up the majority of the capital expenditurein such projects. One solution considered previously is simple co-gen-eration of electrical power using a binary Organic Rankin Cycle (ORC),which exchanges heat from produced fluids for electrical power[21–25]. Such ORC units featured in several pilot studies in the US(Pleasant Bayou, Texas [21,22]; Teapot Dome Field, Wyoming [23])and China (Huabei Oil Field [24,25]). Although such studies have beenvery useful, power generation from geothermal fluids with ORC tech-nology as a stand-alone project is only competitive with US grid pricesif boiling liquid is produced by the wells at a rate of about 100,000bbls/day [11]. Such well rates are normally never achieved in onshorehydrocarbon production. For example, the pilot project for geothermalviability conducted between 1979 and 1990 in a geo-pressured zone atPleasant Bayou #2, a Texas Gulf Coast well, produced 10,000 bbls/day(292 gpm) with BHT of 154 °C (309 °F) and brine surface temperature of136 °C (279 °F) [26]. Geo-pressured resources, unlike common hydro-thermal resources, commonly contain gases like methane [27]. ThePleasant Bayou pilot suggested power generation with an ORC unit andwas economically viable if optimistic assumptions were made aboutsimultaneous gas sales [21,22]. Brine production rates in the geo-pressured zone vary between 10,000 and 40,000 bbls/day [28] and arerelatively high as compared to other oil and gas producing reservoirs,but such rates remain sub-commercial for stand-alone power generationprojects [11]. A separate economic assessment of a small ORC field unitpowered by LT brine suggests such units can replace diesel poweredgenerators (@$0.50/kWh) in remote well locations where grid power isunavailable [29].

The potential of repurposing abandoned oil and gas wells by low-ering, into the reservoir, a well bore heat exchanger (WBHX) has beenexplored in several previous studies [12,17,19,20]. Such studies havemostly focused on direct-use applications; power generation is notcurrently deemed competitive with fossil-fuel based electricity cost[31,32]. Separately, geothermal energy extraction using EGS strategiesby injection of water and re-circulation in oil and gas wells with ex-pansive fracture systems were concluded unlikely to be economic atcurrent electricity prices [34], but this may change in the future. Theeconomic viability of technical recoverable geothermal resources de-pends upon whether the extracted energy can compete with the cost ofusing traditional forms of energy supply. With traditional energy supplysystems favorably priced due to (1) mature infrastructure and (2) risk-free application of proven technologies, the commercial extraction ofLT geothermal energy remains largely unproven. For example, elec-trical power supply cost in the US typically ranges between $0.10 and$0.20/kWh [7]. The commercial exploitation of shallow LT hydro-thermal reservoirs for power supply in the western US (with the highend electricity prices) is made possible by geothermal fields with highwater production rates (about 100,000 bbls/day per well), at suffi-ciently high temperatures (just under 150 °C), and the occurrence ofsuch resources at relatively shallow depths (about 1 km deep) [11].

The economic development of abandoned oil and gas wells atcommercial basis remains unproven. However, multi-million dollar,hydraulically fractured oil and gas wells tap into oil and gas maturitywindows between 8000 and 12,000 ft deep (Barnett, Eagle Ford,Marcellus) and are even deeper in the Haynesville shale play, wherewells typically reach 18,000 ft deep. What has been pre-emptive for oiland gas operators to assume the risk of repurposing abandoned hy-drocarbon wells for geothermal energy extraction is that the majority of

Fig. 1. Geothermal resources of the United States heat map indicating howfavorable an area is for development of those resources [8].

Fig. 2. Active horizontal wells in US shale plays near major population centers[1]. Shale plays are Austin Chalk/Woodbine (Houston), Eagle Ford (San An-tonio), Marcellus (Pittsburgh), Woodford (Oklahoma City) and Niobrara(Denver).

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those wells are located in the SE part of the US where crustal heat flowtypically is lower than in the western US. Due to absence of known hightemperature (HT) hydrothermal systems, the geothermal potential ofTexas has not been included in any previous geothermal resource es-timation by the United States Geological Survey [9]. However, thebottom-hole temperature in shale wells are in excess of 200°F, whichprovides access to valuable geothermal resources. An independent as-sessment of the geothermal energy in Texas found there to be over1.3×1024J of geothermal resource in place under the state, with thelargest amount concentrated along the Gulf Coast [10]. Bottom-holetemperatures of many oil and gas wells in Texas will easily reach the240 °F as a prerequisite for economic exploitation (Fig. 3). The currentchallenge is to develop pilot projects that demonstrate economic via-bility of well conversions for geothermal energy extraction. Economicevaluation tools exist for generic geothermal project evaluation[35–38]. The present tool is developed specifically to assess the con-version of abandoned oil and gas wells.

2.2. Texas A&M RELLIS Campus geothermal feasibility study

The RELLIS Campus (College Station, Texas), a new extension of theTexas A&M University System (TAMUS), will be redeveloped as a stateof the art facility, with a stated aim to include the use of renewableresources. Beneath the campus occur several hydrocarbon plays.TAMUS administers the mineral rights of the RELLIS campus, whichincludes the Eagle Ford Shale, Austin Chalk and Buda Limestone playsthat produce oil and - to a lesser degree - natural gas. Several wellswhich targeted this play are nearing the end of their economic life andcreate excellent candidates for repurposing as a geothermal resource[39]. Table 1 displays the reference codes, key parameters and status ofthe wells studied.

There are currently 12 deep oil and gas wells beneath the campus, 4of which are inactive when our study began early 2017, of which 2wells have recently been plugged and abandoned (P&A; Table 1). TheRELLIS Campus is outlined in Fig. 4a–c along with the horizontal wells

located beneath. In a very important first step, we have obtained re-levant initial data on the wells and statements of support from thecurrent operator to use some of these wells for a geothermal feasibilitystudy. The ultimate goal of this project would be to procure ServicePurchase Agreements (SPAs) from the various tenants on the campus tosupport the development of a geothermal space conditioning system asan alternative to a standard, grid-powered HVAC unit.

To produce geothermal energy, it is imperative that the operator hasthe rights to do so [40]. Therefore, the main entity in this business is thegeothermal operating company. Based on Federal and Texas state laws,the rights to geothermal resources lies with that of the mineral rightsholder. The project will pay royalties to the owner of these rights forextraction of the geothermal resource. As of today, no geothermal leasehas been granted to any party in the state of Texas [39]. In Texas, mostof the licensing and permitting process would be done through theTexas Railroad Commission (RRC) and would require first establishingthe company as an organization and then transferring the geothermaltarget wells into that company's portfolio. This new entity would berequired to file a permit for one or more injection well(s). Once thegeothermal system is operational, the company would be required tosubmit a monthly geothermal production report as well as an annualreport for the injections showing what volumes/pressures wereachieved each month of the year for the filing [2]. Additionally, theremay be a requirement for environmental/groundwater filings de-pending on well location/production type.

The income for the leasehold operator consortium would be gen-erated from the space-conditioning system based on service contractswith end-users. Assuming a chiller-based space-conditioning system atthe surface (Fig. 5), the basic system necessitates a heat source for theworking fluid (from the geothermal reservoir) and a pump system to becycled through it. The fluid streams are controlled via smaller pumpsfor the surface flows and a larger pump to cycle water from the geo-thermal reservoir. The hot water from the reservoir would be held in aninsulated tank on the surface and would be refreshed from the reservoiras needed via the larger pump. Heat is extracted from the chilled water

Fig. 3. Isotherm maps for East Texas at 6 different depths between 8000 and 13,000 ft, based on well data (adapted from Blackwell et al. [30]). The RELLIS Campus islocated in Brazos County, adjacent to Grimes County, marked on the 12,000 ft isotherm map.

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stream until it is at a suitable level to be flowed through the space to beconditioned at which point air is circulated over the chilled watercreating cool air. As with a standard HVAC unit, power will be requiredto run the ancillary equipment; in this case the pumps and the elec-tronics on the chiller itself, which are an operating cost, that is includedin the present assessment. The project will pay royalties to the owner ofthe geothermal rights (TAMUS) for extraction of the geothermal re-source.

2.3. Project assessment methodology

The case study adopted for our economic analysis considers a space-conditioning system driven by a geothermal energy supply system thatextracts subsurface heat via abandoned oil and gas wells. A spreadsheettool takes all inputs to evaluate the key performance indicators for eachproject stage as an aid for decision-making and deal structuring. Eachproject stage and development steps therein are explained in detailbelow, with examples of how the spreadsheet tool can aid in the deci-sion-making process. The methodology of this study is split into threedistinct parts:

Table 1Data on wells completed in the RELLIS lease area.

Symbol API (*) Number Formation Date of Completion Vertical depth (ft) Lateral Length (ft) Total length (ft) Status

R1 42-041-31502 Austin Chalk 01 Jun 1991 7802 3258 11060 InactiveR2 42-041-31504 Austin Chalk 01 Nov 1991 7628 4793 12421 P&A Jan 2018R4 42-041-31543 Austin Chalk 01 Dec 1991 7628 4233 11861 ActiveR3 42-041-31512 Austin Chalk 01 Apr 1992 7844 3566 11410 ActiveR6 42-041-31656 Austin Chalk 01 Oct 1992 7856 3904 11760 InactiveR5 42-041-31584 Austin Chalk 01 Nov 1992 7630 2508 10138 P&A Jan 2018R 42-041-32419 Eagle Ford Shale 01 Apr 2014 8240 8630 16870 ActiveO 42-041-32224 Eagle Ford Shale 01 Apr 2014 8240 2942 11182 ActiveM 42-041-32332 Eagle Ford Shale 01 Nov 2014 8240 6550 14790 ActiveH1 42-041-32331 Eagle Ford Shale 01 Nov 2014 8240 5950 14190 ActiveH2 42-041-32469 Eagle Ford Shale 01 Jan 2018 8240 7905 16145 ActiveH3 42-041-32470 Eagle Ford Shale 01 Jan 2018 8240 7359 15599 Active

API (*) = well number identification according to the American Petroleum Institute; 42 refers to the state, TX, in our case, and −041 refers to the county, BrazosCounty, in our case, followed by the well number within the county.

Fig. 4. a: Map view of the Texas A&M RELLIS Campus with oil well sites highlighted. b: RELLIS wellbore trajectories. The white arrows represent where on thesurface each well was drilled from. The dotted outline represents the landing zone. Wells labeled R, O, M, H1, H2, H3 are completed in the Eagle Ford Shale and wellslabeled Riverside R1 to R6 are Austin Chalk wells. The rectangular panel shows the portion of the gun barrel view given in c. c: Gun barrel view of all the hydrocarbonwells completed in the RELLIS lease area. Vertical axis is 10x exaggerated.

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1. The first stage (Section 3) is the technical module (Section 3), whichcovers the subsurface assessment and technical solution for energyextraction. The module seeks to understand the geothermal reservesof a formation, the transfer of those heat reserves to a working fluid,the delivery of that fluid to the surface and the ability to convertthose fluids to usable energy.

2. The second stage (Section 4) is the economic module for the geo-thermal utilization system, which attempts to account for the ex-tensive uncertainty in the preliminary study through Monte Carlosimulation. The essential input parameters are represented by dis-tribution functions to account for the uncertainty.

3. The third stage (Section 5) evaluates possible commercial dealstructures that would make a geothermal space conditioning serviceattractive for the investing parties. Possible partnership structuresare evaluated in terms of return on investment to each party, whichinformation could be used in discussions with interested parties toavail the economic benefits to those involved. Three project stagesdelineate increasing project maturity: (1) feasibility study, (2) pilotproject, and (3) full-scale development.

3. Technical module steps

The methodology used in our study to construct the spreadsheet-based decision making tool is explained in three stages (see overview inSection 2.3, above). Stage 1 defines both the subsurface and surfaceconsiderations and comprises three steps. Step 1 is a rough volumetriccheck of geothermal energy in place (Section 3.1). Step 2 describes theheat transfer from the reservoir to the circulating working fluid andaccounts for heat loss as the fluid rises to the surface (Section 3.2). Step3 is the heat exchange of that fluid on surface within the chiller (Section3.3).

3.1. Step 1: Estimation of original geothermal energy in place

The volumetric check of geothermal energy in place follows anapproach adapted from Lachenbruch [41], which essentially accountsfor the heat capacity of any reservoir rock and its reservoir liquids, andscales the stored energy amount based on reservoir size. The geothermalenergy in place is:

= − + −E ρ c Ad ϕ ρ c Adϕ T T[ (1 ) ]( ) [kcal]I M M L L R A (1)

with ρM =specific gravity matrix, cM =specific heat matrix, A=reservoir area, d= thickness; ϕ =porosity, ρL =specific gravityliquids, cL =specific heat liquids, TR =reservoir temperature, and TA=ambient temperature.

Several other geothermal resource in place approaches have beenproposed [9,42], but essentially these use the same principle as La-chenbruch [41]. The classification of geothermal energy resourcesconsiders the theoretical potential (energy in place), technical potential(technically recoverable energy), and economic potential (fraction ofthe geothermal resource in place that can be commercially extractedwith current technology) [43,44]. In our study, economic potential isassumed to imply sustainable development is secured. The USGSmethodology can also be applied [9,42] and will yield similar results.However, we do not favor a proposed methodology with rejection ofimpenetrable reservoir sections [45], because such section could bepenetrated in the future with hydraulic fracturing.

Values for thickness, drainage area and porosity are based on roughaverages for the area [46,47]. Another critical input for Eq. (1), inaddition to the reservoir volume estimation, is the reservoir tempera-ture. Based on information from the well's current owner at the RELLISCampus the target reservoir has a temperature of ∼237°F (∼114 °C).Other information used in the geothermal energy in place estimationare estimates based on what is known of the Austin Chalk formationwhere the well is located. The liquid is assumed to be a brine (∼15%NaCl) [33] and the rock matrix is assumed to be predominantly calciumcarbonate. Fig. 6 is a screenshot of the energy in place calculator em-bedded in our spreadsheet tool. The inputs used are estimations givenfor a 40 acre well drainage region of a 20 ft thick section of the geo-thermal host rock.

3.2. Step 2: Reservoir heat transfer model

The heat transfer within the reservoir to the refrigerant fluid hasbeen modeled by Zuo and Weijermars [48], which indicates that theviability of a geothermal EGS project critically hinges on three basicaspects of the heat transfer process: (1) Achieving circulation rates of aworking fluid with well production rates in the order of 10–100 L/s, (2)Extracting such fluid volumes with an appropriate temperature, in therange of 100–150 °C, and (3) Maintaining both the flux and the tem-perature over a 20–30 year life-cycle required for any commercial heatconversion project. Zuo and Weijermars [48] provide metrics for

Fig. 5. Schematic of geothermal space conditioning system.

Fig. 6. Original geothermal energy in place calculator input/output panel.

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collaborating the longevity of brine temperatures in a simplified, butscalable EGS design, for a range of circulation rates. The model revealedthat a fractured geothermal reservoir will not achieve a steady stateEGS temperature. The heat transfer process from fractured wall to theworking fluid will decline over time depending on several factors in-cluding contact area, duration of continuous flow and fluid tempera-ture. To prevent premature decline of the reservoir temperature and cutoperating cost, the daily pumping schedule varies with HVAC operationhours requirement (see Section 3.4).

For the sake of this scoping study, a simple log-normal declinefunction is used to simulate the long-term decline of the reservoirtemperature, TR, using a reservoir efficiency factor, REF, to assesstemperature decline profiles as a function of time, t, in months:

= ∗T t TREF

REF t( ) ( ) [deg C]RRi

i (2a)

The Reservoir Efficiency Factor (REF) is given by:

= − +REF t t REF( ) ln( ) [unitless]i (2b)

The reservoir temperature decline profile from Eq. (2a) is used todetermine what will be the effective fluid temperature over the life ofthe project. A log-normal decline function was used to simulate therelatively rapid early decay of reservoir temperature, which slows downwhen the differential between the working fluid and the temperature ofthe fracture system narrows. A more detailed model of temperaturedecline is being constructed [48], which eventually can be used to re-fine the log-normal function used in the present study. The effectivefluid temperature is not simply the reservoir temperature at bottom-hole level. The fluid flowing from the reservoir will lose a portion of thebottom-hole flowing temperature by the time it reaches the surface.Additionally, the working fluid may not necessarily have adequate timein the reservoir to reach the ambient reservoir temperature.

The previously commercial, and soon to be re-released, GTEMPsoftware is a suitable candidate for modeling temperature losses from afluid in a wellbore [49]. The GTEMP model considers wellbore trajec-tory, construction, fluid properties, matrix properties and operatingconditions to establish the temperature profile of the flowing fluid.GTEMP models convection and conduction within the wellbore as wellas heat conduction within the surrounding rock formation. At eachdepth of the well, three temperatures are modeled: the fluid tempera-ture in the tubing, the fluid temperature in the annulus and the tem-perature of the surrounding rock formation [49]. Once additional de-tails such as casing program, tubing material and specific formationdepths/thicknesses are known, the GTEMP model will yield a specificestimate of fluid temperature as it surfaces.

For the sake of this scoping study, a simple fluid heat loss factor dueto transport in the wellbore is applied to the temperature of the re-servoir fluid. The transport heat loss factor is gradually decreased overtime as it is understood the delta between surface and bottom-holetemperatures should diminish after circulation has occurred for a pro-longed period [50]. For simplicity, it is assumed that the wellbore fluidheat loss factor (FLF) will decline in a similar fashion as the reservoirtemperature model of Eq. (2a):

= ∗FLF t FLFREF

REF t( ) ( ) [unitless]i

i (3)

The temperature of the produced fluid, Tf(t), is assumed to never beless than the ambient temperature, TA(t), when circulated downhole.

= − ∗ − +T t T t T t FLF t T t( ) [ ( ) ( )] [1 ( )] ( ) [degC]f R A A (4)

Eq. (4) includes the result for TR(t) as determined by Eq. (2a).Subsequently, the geothermal energy recovered from the reservoir as afunction of time can be defined as follows:

= −E ρ c q T FLF t˙ [1 ( )] [Kcal]Q L L L t R t( ) ( ) (5)

The thermal energy, EQ, acquired from the reservoir is considered

additive due to the energy content resulting from the fluid's initialtemperature. Fig. 7 shows the long-term reservoir temperature declinecurve (blue curve) using Eq. (2a), produced fluid temperature (orangecurve) based Eq. (4) and cumulative geothermal energy produced[yellow curve as per Eq. (5)].

Calculating the total energy produced for the life of the project(Fig. 8) should yield a result that is significantly less than the originalgeothermal energy in place (Fig. 6). The data used are estimates validfor the median case for the RELLIS Campus project. Our conclusion isthat over the 25-year project life, 1.2× 109 kcals are consumed in theproject (Fig. 7), as compared to the available 2.4× 1011 kcals availablefor the 40 acre well spacing (Fig. 6) or less than 0.5% of the originalenergy in place. Additionally, through the use of probabilistic inputdistributions, rather than discrete values, we investigated the range oftotal energy produced from the project in a Monte Carlo simulation.Fig. 8 shows the output distribution. From this stochastic analysis wedetermine with a P99 level of certainty that the maximum energyproduced and consumed in the project would be 1.7×109 kcals, whichis less than 1% of the available energy in place.

3.3. Step 3: Surface equipment

Once the temperature of the produced geothermal fluid is predicted,the temperature profile for the life cycle of the project (Fig. 7) can beused as an input to the surface equipment. The required surfaceequipment capacity in part depends on the climate zone in the US. Thespreadsheet tool provides for flexible capacity of the space-conditioningsystem for a certain built space footage, scaled based on US climatezoning (Fig. 9), which affects the tons of refrigeration required. The

Fig. 7. Reservoir and produced fluid temperature (left scale) and cumulativeenergy (right scale) over during the course of the project. The producing fluidtemperature is cyclical due to the diurnal pumping schedule.

Fig. 8. Normalized probability density distribution (vertical scale) of the cu-mulative energy produced (horizontal scale) during a 25-year project life.

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climate zones define a climate for each county in a state and based ontemperature variations using Heating Degree Days (HDD) and CoolingDegree Days (CDD).

The selected chiller unit with a certain maximum refrigeration ca-pacity will operate at different efficiencies depending on the workingfluid temperature input [51], as detailed in Fig. 10. The utilized re-frigeration output for the particular temperature of the fluid recoveredfrom the reservoir determines how frequently the system must run tomeet the cooling specifications for the space considered. The datapoints in Fig. 10 were taken from a manufacturer documentation andthen a second order polynomial function was fit to allow for continuouscalculations of chiller efficiency. Due to the nature of the chiller po-tentially being less than 100% efficient, it may be necessary to outfit theproject with a chiller size larger than a standard heating, ventilation,and air conditioning (HVAC) unit. A safe margin should allow for theunit to potentially operate at only 60% efficiency, yet still be able tocool the space.

The standard estimates for diurnal operation hours each month for atypical HVAC unit in College Station, TX, are specified in Table 2. Thespace to be climate conditioned will be populated by many people andcomputers giving off additional heat so the required refrigeration wouldbe higher than for the average home. To help account for uncertainty,the basic input values of Table 2 are given input distributions in thefinal spreadsheet model (i.e., January is triangular distribution with a

min of 3, mode of 4 and max of 5 h). Additionally, the diurnal operationhours can be adapted dependent on the Climate Zone selected in theproject properties area (Fig. 9). The daily operating hours required forthe adsorption chiller running on geothermal energy are defined as:

= ∗hrs hrscap t

TonsTons( )

[hours]oppstd std

ad (6)

With hrs =hours operating in a day, cap t( ) =capacity of ad-sorption chiller at given time t in months [decimal], sub-script std =standard HVAC unit, and subscript ad =adsorptionchiller.

The reservoir temperature (Fig. 11a) and produced fluid tempera-ture (Fig. 11b) in the final month of the 25-year RELLIS campus testcase were computed based on Monte Carlo simulations. In our model,there is a P90 level of certainty indicated by the Monte Carlo simulationthat the final produced fluid temperature will be at or above 75 °C(Fig. 11b). Based on that value, it can be read from Fig. 10 that thechiller capacity utilization will be about 75%. This means the systemhas more than adequate capacity and will only need to function afraction of the time.

4. Methodology: economic module steps

The economic modeling in the spreadsheet evaluation tool devel-oped in this study, which models the project cash flow, deal structureand financial metrics, comprises three steps. Step 1 considers the inputsused for the distribution ranges for the cash flow variables (Section4.1). Step 2 sets up a deal structure in terms of project timeline andownership working interest (Section 4.2). Step 3 is a basic cash flowmodel linked to a Monte Carlo simulation, which generates a dis-tribution of possible financial results (Section 4.3).

4.1. Step1: Distribution inputs for economic model

Fig. 12 illustrates the various inputs used for the economic model.The first two items have been discussed in the previous section sur-rounding the subsurface uncertainty. The next three items (greyed out)are calculated values based on the size of project to be scoped. Theestimates for these values come from distributors for the products [52]and reported industry norms [53]. The Chiller Cost (Fig. 12) describesthe cost of an adsorption chiller as a function of tonnage. The SurfaceEquipment Costs are the costs for the surface pumps which will drivethe hot, cooling and chilled water streams through the adsorptionchiller. The Comparable Chiller Costs describes the cost of the economicalternative (grid-based HVAC system) against which the geothermalsystem will be evaluated. In the present study, the end-users are notpurchasing the HVAC equipment as would be the case in a standardmodel, but rather receive the space conditioning system functionality asa billed service. This suggested business model would be analogous to

Fig. 9. Project properties selection is based on the location in the climate zones.The RELLIS project is in Zone 5. The spreadsheet algorithm allocates an 18 tonrefrigeration capacity for the HVAC unit for a 10,000 sq ft pilot space.

Fig. 10. Adsorption chiller refrigeration capacity at a given inlet temperaturewith a polynomial curve fit for x and y axis values [47].

Table 2Assumed HVAC unit daily operating hours bymonth.

Month Hours operating

Jan 4Feb 6Mar 8Apr 10May 11Jun 12Jul 12Aug 12Sep 10Oct 8Nov 6Dec 4

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purchasing traditional electrical power as opposed to owning a smallpower plant, or leasing the supply of a solar panel from a provider bypurchasing green electrical power.

The final seven inputs (Fig. 12) are variables depending on wellselection, local costs/prices and operational knowledge. The first is anefficiency factor applied to the Comparable Chiller, commonly referredto as a Seasonal Energy Efficiency Ratio (SEER). Ultimately, this boilsdown to what is the total kWh(s) required to produce a ton of re-frigeration [54]. Next line item is the standard charge from the electricgrid for electricity. This electricity cost is incurred to run the surfaceequipment for both the adsorption and standard chillers. Electricityprices vary widely across the US [7] and depend on the project's geo-graphical location and may vary over time and as such need regularupdating (EIA publishes US regional variations in monthly grid prices).The Fixed Opex number is simply the average monthly cost of main-tenance/repair on the geothermal HVAC system. The Well Pump Op-erating Time is the percentage of time that the large Well Pump willneed to run, cycling hot water from the geothermal reservoir to thesurface process train. Pump operating time is affected by several fac-tors, and extracted based on Fluid Temperature Loss Factor, insulationof any holding tank(s) and ambient temperature to name a few. TheSurface Pump Power is the combined power of the pump unit(s) movingthe hot, cooling and chilled water on the surface. Well Pump Power isthe horsepower of the pump that will circulate the fluid from thegeothermal reservoir to surface. The size of this pump is a function offrictional losses from wellbore contact (i.e. a deeper/longer well willrequire a larger pump). The last input (Fig. 12) is the general and ac-counting (G&A overhead) cost paid by the Operating Company.

Each of the inputs specified in Fig. 12 is treated as a triangulardistribution which requires a minimum, most frequent and maximumvalue. Some of these values contain correlations to each other. Forexample, a correlation may exist between cost of a standard chiller andthe efficiency of it, which is assigned a value of 0.8 R2, where a more

expensive chiller is more efficient. More correlations will likely develop(i.e. Well Pump Operating Time versus Fluid Temperature Loss Factor),however the nature of those correlations is unknown at this point andwill require experimental data to confirm.

A final check built into the spreadsheet inputs is the inclusion of a‘Throwaway’ variable. If for a given iteration the combination of inputsyields a produced fluid temperature that is, at any time, below what isrequired to operate the adsorption chiller with the required minimumefficiency (Fig. 9), then that iteration is tagged as a ‘Throwaway’.Fig. 13 shows that a higher Fluid Temperature Loss Factor combinedwith a lower Reservoir Efficiency Factor leads to a line of demarcationfor a ‘Throwaway’ occurring.

The principal outcome of Step 1 in the economic assessment is thedetermination of the rate (cost per kWh) that needs to be negotiatedwith end-users in a SPA for the operator to still reach a desired returnon investment. Subsequently, the SPA target rate allows the end user tomake a direct comparison with the cost of a standard HVAC system.Separately, the SPA rate of the geothermally-driven space-conditioningsystem commensurate with a specified IRR is obtained by applying thegoal-seek computation loop outlined in Fig. 14.

4.2. Step 2: Commercial partnership structure

To fully evaluate the commercial perspective of the project it isimportant to include in the evaluation tool the returns for all of thepartners that bear a financial interest in the economic performance ofthe project. The partnership structure needs a specification of timelines,

Fig. 11. Normalized probability density distribution (vertical scale) for the final temperature (in Celsius) after 25 years for (a) the reservoir fluid and (b) theproduced fluid.

Fig. 12. Input panel for distribution of variables used in the Monte Carlo si-mulation of economic performance.

Fig. 13. Cross-plot of Reservoir Efficiency Factor vs. Wellbore FluidTemperature Loss Factor correlation to 'Throwaway' occurring.

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phases of final investment decisions (FIDs), working interest sharedistribution, royalties due and possible grant capital. Fig. 15 shows thelikely project Phases A-D, including the pertinent FIDs as they relate tothe project phases.

The overall project timeline has four major phases. The first ofwhich is the Project Identification (Phase A), which includes site se-lection. During Project Phase A, there is no capital spent in the form oftangible assets, this is strictly the time during which there is initialtechnical scouting to find a suitable geothermal site and an interestedinvestor along with a potential market. Procuring a MOU for a PSA froma potential end user will likely be necessary at Phase A. The MOU wouldprovide an indication for inputs required for the cash flow model, in-cluding a certain hurdle rate. Failing the ability for the project toachieve this hurdle rate due to underperformance of the reservoir orother issues, the agreement would become null and void.

Assuming the scouting of Phase A is a success, the new GeothermalOperating Company is formed and the surface equipment is purchasedto begin testing the performance of the reservoir. This Project ScopeTest (Phase B) would perform a well test by hooking up a pump andcirculating fluid to obtain a much better picture of what surface fluidtemperatures could be delivered from the geothermal reservoir. Thisequipment purchase would constitute FID I (Fig. 15), which is takenafter the completion of Phase A and a prerequisite for Phase B. Costs forthe execution of Phase B are split between the Investor and OperatingCompany based on the agreed Partnership Interest percentages in thePhase B partnership structure (Fig. 16). Phase B would also utilize anycapital from any grants received to offset the earliest project costs(assuming the specific grant allows it). In the spreadsheet tool, there isroom for a specific grant to offset startup cost, specifically used towardsthe costs of the surface equipment. If the Project Scope Test (Phase B)

has a successful outcome, FID II is taken before the start of ProjectPhase C (Fig. 15), which would encompass the purchase and surfaceinstallation (adsorption chiller and associated assets) (Fig. 16). Cost forthese assets and their installation would be split according to thePartnership Interest percentages agreed for Phase C in the partnershipstructure. The partnership percentages given in Fig. 16 are examplesand can be varied, the spreadsheet will automatically update and adjustthe resulting benefits for individual partners (see Section 5 for details).

Project Phase C consists of the substantial completion of the chillerinstallation, pump fitting and other operational infrastructure (Fig. 15).Ancillary options to investigate include: (1) Solar heating of the hotwater tank on surface; (2) Capture of heat generated by the well pumpto increase surface water temperature; (3) Additional surface equip-ment installations to take care of other building functions like heatingin the winter and year-round hot water; (4) Installation of oil/waterseparator to extract residual hydrocarbons. Upon successful completionof Phase C, and entering Phase D, the Geothermal Operating Companybegins generating cash flow and royalties due to the Geothermal RightsHolder (Fig. 16, Phase D). The royalty percentage during Phase D isdifferent before payout (BPO) and after payout (APO), which is whenthe total project has paid back the capital spent. After the royalty hasbeen paid to the Geothermal Rights Holder, the remaining revenue lesscosts (profit) is split between the two remaining Partnership Interestholders, based on the structure and percentages agreed for BeforePayout (BPO) and After Payout (APO) (Phase D, Fig. 16). For example,if the current month's revenue were $1000 with $500 in costs and thestructure at the time had a 10% Royalty and Partnership profit split of50/50 between two parties, the payouts would be as follows: to RoyaltyOwner: $1000 * 10% = $100; to Working Interest Partners: ($900 -$500) * 50% = $200 (each).

Fig. 14. Monte Carlo decision-making model based on economic performanceof project. Assume a service rate (top left), the spreadsheet will iterate andmodify the service charge with a goal-seek function to achieve a 10% IRR.

Fig. 15. Overview of project phases and Final Investment Decisions.

Fig. 16. Input area for timeline of project and ownership interests during eachphase.

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4.3. Step 3: Total cash flow model

Step 1 has provided the service charge rate and Step 2 has providedroyalty and profit sharing percentages for the project partners, based onreasoned decision-making criteria captured in the spreadsheet tool. Thevalues determined in Steps 1 and 2 are next used to create a basicproject cash flow model:

= + +Net Cash Flow Capex Opex Revenue( ) ( ) [$] (7)

= −Capex Surface Equipment Chiller Grants( & ) [$] (8)

⎜

⎟

⎜

⎟

= ⎛⎝

∗ ∗ ∗

∗ ∗ ⎛⎝

⎞⎠

∗ ⎞⎠

+ ⎛⎝

∗ ∗ ∗ ∗

⎛⎝

⎞⎠

∗ ⎞⎠

+

Opex

Well Pump Power hp kWhp

hrs Well Pump Operating

daysmonth

Grid Power Cost centskWh

dollarscents

Surface Pump Power hp kWhp

hrs daysmonth

Grid

Power Cost centskWh

dollarscents

Fixed Opex

( ) 0.746 (%)

30.44 0.01

( ) 0.746 30.44

0.01 ($) [$]

opp

opp

(9)

⎜

⎟

= ⎛⎝

∗

⎛⎝

⎞⎠

⎞⎠

∗ ∗ ∗ ⎛⎝

⎞⎠

∗ +

Revenue

Tons Refrigeration Required Tons Comparable Chiller

Efficiency kWTon

hrs daysmonth

Assumed Rate centskWh

dollarscents

Fixed Opex

( )

30.44

0.01 ($) [$]

std

(10)

The outcome of the project cash flow model includes options to splitthe costs and revenue to the three basic Partnership Interest entities(Fig. 16), depending on the phase of the project as outlined in Section4.2. Once the cash flow for the project and the three entities is calcu-lated, metrics such as Internal Rate of Return (IRR) and Net PresentValue (NPV) can be used to evaluate project's economic viability.Fig. 17 specifies the payout for each partner, based on their cumulativenet cash flow. Fig. 18 accounts for the uncertainty in the total projectNPV distribution at 10% discount rate.

A common performance indicator used in this type of industry isnormalized cost in terms of NPV10/sq ft. This is the present value of thecash flows discounted at 10% per square foot of space to be condi-tioned. This benchmark value is calculated, in the spreadsheet tool, forboth the geothermal space conditioning system solution and a standardHVAC solution. Eq. (11) shows the basic form for calculating the

standard solution costs:

⎜

⎟

= ⎛⎝

∗

⎛⎝

⎞⎠

⎞⎠

∗ ∗ ∗ ⎛⎝

⎞⎠

∗ +

Standard Chiller Costs

Tons Refrigeration Required Tons Comparable Chiller

Efficiency kWTon

hrs daysmonth

Grid Power Cost centskWh

dollarscents

Fixed Opex

( )

30.44

0.01 ($) [$]

std

(11)

Ultimately, the key metric for the project is calculated as a cents/kWh needed to charge to the end-user in order for the project partnersto make a certain rate of return. The SPA charge is determined by theset IRR objective (Fig. 14). However, the partitioning of the profits andinternal rates of return between the project partners will be subject tonegotiations and the deal structure and are factored into the IRR outputwindow (Fig. 19). Tradeoffs and negotiation driven objectives can beanalyzed with the spreadsheet, making it a valuable decision-makingtool as separately highlighted in Section 5.

4.4. Sensitivity analysis

Moving beyond the required cost of power, a sensitivity analysiswas built into the spreadsheet tool in order to reveal which variableshave the most significant impact on the project economics. In all eco-nomic analyses, it essentially boils down to a choice between alter-natives. Assuming that the space will be built and it will require con-ditioning, the alternative to the geothermal solution is the standardsolution comprised of HVAC powered by the cost of grid price elec-tricity. To better understand the variables which affect costs of eachsolution, the sensitivity analysis of Fig. 20a and b compares each caseside-by-side.

The tornado charts (Fig. 20) depict the impacts of variables by effecton the mean NPV10/sq ft. A couple of important insights can begleaned from these charts. First, the standard, grid-powered HVAC so-lution has an overwhelming top impact variable: the cost of power fromthe grid (Fig. 20a). Not surprisingly, higher electrical power prices willincrease the cost to chill the space. For the geothermal solution, var-iations in the Well Pump Operating Time and Well Pump Power havethe largest impact (Fig. 20b). Therefore, early efforts should be

Fig. 17. Monthly increase of cumulative cash flow for the partnership structureassumed in Fig. 16 for the RELLIS Campus project. Payout month for eachpartner is indicated by vertical line marks, after which cumulative cash flowturns positive for each.

Fig. 18. Normalized probability density distribution (vertical scale) for projecttotal NPV10 (horizontal scale).

Fig. 19. IRR for each party based on a given SPA rate entered in the green box.

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undertaken by the operator to optimize these variables. If done cor-rectly, the operator may realize a significant increase in base case IRR.

Another significant difference occurs in the range of potentialNPV10/sq ft between the two solutions (Fig. 20a and b). The standarddeviation of the green, geothermal solution is three times higher thanfor the standard chiller. This is not surprising given the ‘newness’ of theproposed geothermal solution as well as the uncertainty factors sur-rounding it. Nevertheless, it is important to quantify such uncertaintysince it translates to an investment risk that will need to be accountedfor when discussing with potential investors or customers.

We have scoped out this project for a 10,000-square foot (sq ft)building near College Station, TX. All of the input variables (for boththe technical and economic modules) have been selected to suit thisarea as best as possible given current understanding of the subsurfaceconditions, wellbore placement and end-user requirements. Based onthe parameters for the RELLIS campus the estimated maximum projectsize corresponds to the reservoir capacity, loss factors and facility so-lution equates to roughly 2.411 kcal or 4MW of power per 40 acres,assuming a 25-year life and average chiller unit runtime of 8 h per day.For this study, it is assumed that the area to be cooled is 10,000 sq ftand will require ∼20 tons of refrigeration based on the local climate asshown in Fig. 9 [55] or 70 kW [56]. We conclude there is ample geo-thermal energy available even when assuming a relatively conservativerecovery/efficiency rates in our model inputs.

Using input parameters displayed in Fig. 12, and assuming a certain,negotiated deal structure (Fig. 16), @Risk was activated to solve for theservice charge rate to the HVAC end-user required to guarantee a 10%IRR to the operator (Fig. 14). Exactly 1000 iterations were run for thissimulation. None of the 1000 iterations yielded a ‘Throwaway’ itera-tion, which ascertained that the reservoir can provide the requiredenergy for the full 25-year project life.

The histogram in Fig. 21 illustrates the range/distribution of SPAservice rates required to be charged to the end-user, assuming thegeothermal reservoir is performing as planned. A mean value of ∼17cents/kWh can now be used as a basis for offering a SPA to potentialcustomers of the system. In terms of probabilities for project success,Fig. 21 indicates there is a 50% chance that the operator will achieve a10% or greater IRR if a rate of 17 cents/kWh is offered to the end-users.

5. Project evaluation and execution stages for geothermal fielddevelopment

Evaluation of the commercial structure for the geothermal project isdeliberately set up as a separate module. For this investigation, it iscritical that the range of outcomes is accounted for as best as possiblevia Monte Carlo methods. To avoid burdening and confounding any

potential investors with multiple distribution functions in commercialnegotiations, it is practical to assume a hurdle rate that needs to beachieved for the project (Monte Carlo result), which can then be used asa basis for profit sharing negotiations between parties with the aim tocreate a win-win deal structure that grants each party terms satisfactoryto them. Such information is crucial and relevant for the potential ef-ficiency of any set of viable commercial partnership structures. Also,during commercial discussions it is important to highlight and explainwhat grants/subsidies may be available for the project. As with manytypes of renewable energy, such details can ultimately make or breakthe economic performance of the proposed project.

The decision-making tool developed here can be used throughoutthe development of the three principal project stages: (1) feasibilitystudy, (2) subsequent pilot project, and (3) final expansion in a full-scaleproject of the geothermal development. Each project stage is brieflyexplained below.

5.1. Stage 1: Feasibility study

During the feasibility study stage, project identification (Phase A),resource development solution and its technical and economic appraisal(Phase B), installation performance testing (Phase C), Phase D re-presents the pilot project construction, which includes performanceadjustment based on pre-pilot system tests, and construction of the pilotproject up to the point of material completion (Fig. 15). Prior to thestart of the Pilot Project, in fact, already during Phase B of the

Fig. 20. Tornado diagrams, comparing (a) standard grid driven chiller system cost with (b) geothermally powered (green) solution on the basis of NPV/sq ft.

Fig. 21. Normalized probability density distribution (vertical scale) for the costof power (cents/kWh, horizontal scale) required to ensure a 10% IRR for theRELLIS campus project.

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feasibility study, the initial project partners (operator, investor andgeothermal rights owner) will work out a profit sharing agreement onthe percentage sharing of the capex burden, as well as for the payout ofthe proceeds. This distinguishes Before Project Payout (BPO) and AfterProject Payout (APO) profit sharing, similar to standard contractpractice in US oil and gas projects. Fig. 16 included an example of suchagreed percentages. Note, however, that partners may continue to re-negotiate partnership interest shares during Phase C, preferably notduring Phase D. A firm agreement should already be in place before thestart of Phase D. The anticipated time for completion of Phases A-C,which completes the feasibility study stage, is in our study assumed tobe 13 months.

Note that much of the construction of the installations required forthe pilot project up to the point of material completion is already in-cluded in the feasibility study rather than part of the pilot project itself.This is a deliberate choice, partly because the capex involved is smallenough to justify risking such an investment in the feasibility studystage, and further safe-guarded by FID I and FID II taking place prior toPhases B and C (Figs. 15 and 16), respectively, of the feasibility study.

A unique feature of the tool developed is that it helps the threeproject parties (operator, investor and geothermal rights owner) todetermine the service charge target price for the end-user of the geo-thermal energy provision for a certain pilot project size (say 10,000 sqft building space conditioning) to meet the required project IRR hurdlerate (in this study initially set at 10% for the pilot phase to be approved,but higher IRR is targeted during Pilot Stage validation of all assump-tions, see later). Once the service charge is agreed with the end-user,the three partners can use the spreadsheet tool to determine theirmutual stakes as shown in Fig. 16, while assuring the anticipated cashflow curve attributable to each of them is commensurate with theproject risks. Examples of three possible cash flow partitions workedout during the initial appraisal (Phase B) are given in Fig. 22, withcorresponding screenshots of the deal structure. Note that there are atleast nine different combinations for the ordering of most-middle-leastcash flow recipients among the three project partners.

Fig. 22a favors cash flows attributable to the operator. Fig. 22bfavors cash flows attributable to the geothermal rights holder. Fig. 22cfavors cash flows attributable to the investor company. The agreedprofit sharing percentages also correspond to total capex required toexecute the project is contributed in proportion to the expected cashflow returns to each of the stakeholders. The corresponding IRR attri-butable to each partner is automatically updated when profit percen-tage agreements are shifting during the negotiations. The rough look ofthe lines in the cashflow graph is a function of varying cashflow de-pending on time of year (i.e. summer months requiring large amountsof cooling produce more cashflow than winter months). A close up ofthis effect can be seen in Fig. 17.

5.2. Stage 2: Pilot project

In the feasibility study (Fig. 15, Phases A-C) targets were set for thereservoir performance to meet the IRR hurdle rate of the project. Uponmaterial completion of the installation construction (i.e. at the start ofPhase D), the assumed performance targets will be validated. Thespreadsheet accounts for all parameters relevant for the project per-formance and can be used to adjust parameters, and eventually set moreambitious targets to increase the project IRR, during the Pilot Project.

For example, the largest uncertainties at this point of the study arethe Reservoir Efficiency Factor and Fluid Loss Factor; these parametersare the principal ones to be further validated and improved during thePilot Project. Fig. 23 gives an example of dashboard outputs that thespreadsheet tool generates to help validate whether the project meetsthe required hurdle rate (IRRs). The parameters in Fig. 23 indicatewhich reservoir model output improvements are required to meet theIRR targets for the project partners to decide positively on full-scaleproject expansion. The total time reserved for the Pilot Project (starting

after Phase C, Figs. 15 and 16) is 2 years. During the last quarter of thePilot Project it will be decided whether an expansion into a full-scaleproject is attractive for all three partners. Economic risk needs to bereduced to a minimum, that where agreed which requires final com-mitment by the end-user(s) to sign up for a 25-year Service PurchaseAgreement (SPA).

5.3. Stage 3: Full-scale project

The full-scale project can be negotiated and executed, provided theproject is de-risked both technically (performance of installations andreservoir have been validated during the Pilot Project) and economic-ally (IRR targets can be met with the SPA in place and validatedtechnical performance). The NPV of the project now is increased tomulti-million US dollar scale. The full-scale project may require re-negotiation of the royalty rate(s) due to the geothermal rights holder, aswell as renegotiation of the capex shares and profit shares (APO, BPO)agreed during the feasibility study. The final, full-scale project includesmaterial completion and testing of the up-scaled installations, followedby deliveries to the end-consumers, and the onset of steady cash flowsto the three project partners from the service charges to the end-con-sumers.

6. Discussion

The spreadsheet-based scoping tool developed in our study allowsthe user to identify the major variables in attempting to bring a projectfrom concept to implementation. The analysis can function as a base-line indicator where, given a set of circumstances, the chance forcommercial success can be quantified. Application to our case study ofthe RELLIS Campus Geothermal project indicates the ballpark pilot NPV(discounted at 10%) amounts to about $8 k/well. The pilot projectrequires a capital investment of about $61 k. One well pair may be ableto deliver ten-fold the pilot brine volume with the required minimumtemperature, in which case the NPV/well scales up to $80 k. With30,000 wells currently available near major consumer centers (Fig. 2),the business potential would amount to a $1.2 billion industry in the USalone. The total energy produced by 30,000 wells at target capacity of100,000 sq ft per well would amount to 24 GW. Such a sizable greenenergy contribution would offset high-emission energy supply sources,and substantially contribute to US energy independence by reducingthe need for costly fossil fuel imports. At the same time, second-lifevalue for oil and gas wells will help to sustain or even grow domestic oiland gas production for longer, which will be needed to continue offsetfossil fuel imports in the future.

The model does not attempt to account for the additional upside orefficiencies which are abundant within the project. Optimizing sizing ofpumps, cycle times and tank/piping design are all aspects which war-rant ample review prior to full-scale development. These will only beginto be understood upon conducting the Initial Scoping Study and PilotProject. Additionally, actually flowing fluid through the reservoir andbenchmarking performance will significantly de-risk the projects long-term viability from a reservoir deliverability standpoint. The pilot riskmainly resides in reservoir performance, it must meet the temperaturetargets with decline (in reservoir and well transport) as assumed in thefeasibility study, backed up by a reservoir model in the initial appraisaland to be validated in the pilot study.

Separately, the Pilot Project proposed in this paper for the RELLISCampus has a significant number of positive intangible aspects going inits favor. First, the project is situated in a state that is well-versed insubsurface resource development and has a commercially friendlyregulatory environment. Second, the project is in close physical proxi-mity to the technical/commercial team allowing for a very robustoversight of operations and business development activities. Third, theproject has excellent optics from being both environmentally positiveand sprouting from an academic institution including ample student

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Fig. 22. Initial deal structure sets capex commitments, and cash flow benefits for each partner, under different profit sharing agreements, assuming the requiredservice charge is accepted by the pilot project end-user. Graphs on the right show increase of cumulative cash flow (vertical scale) each month (horizontal scale) forthe partnership structure.

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involvement.Although the RELLIS Campus geothermal project provides and im-

portant testing ground for the Pilot Project, ultimately turning heat intocold is less efficient energy conversion than using heat for heat.Therefore, once the concept is proved, full-development may be moreeconomic in colder-weather climates for use in large-scale space con-ditioning of greenhouses, rec-centers, airports, schools, factories, sto-rage facilities, heating public swimming pools, etc. For the oil and gasindustry, further advancement of these technologies could ultimatelyresult in a system which would be able to power offshore platforms byusing a depleted well to power continued production from other wellstied to the platform. The tool and concepts presented in this paper couldbe adapted for any of these energy projects through adaptation ofvariables (i.e. change cooling to heating) while still maintaining thegoal of determining commercial viability.

The type of unproven geothermal project studied here has manyrisks associated of which the first real one encountered is reservoirperformance. Although every iteration of this model was able to supplythe required power, further technical modeling needs to be undertaken.This uncertainty should diminish as better models are used like the Zuoand Weijermars [48] reservoir assessment model along with the GTEMPfluid temperature model. These models can be calibrated to an evenhigher degree after field trials are completed (Project Phase B, Section5.1). Ultimately, assuming a full-scale deployment is granted after apositive conclusion of the pilot project (Project Phase D, Section 5.2), afield level understanding for such an area will develop where thereshould be a certain degree of tolerance for variations in reservoir per-formance.

As with any type of investment project, insurance should be in-vestigated to mitigate against the unforeseen. This could be costs suchas having to plug and abandon the well before the project has paid outor potential accidents/injuries during operation by the newly formedoperating company. Given the very early nature of project develop-ment, there will be ample opportunity for optimization.

7. Conclusion

The current project proposition would green the image of the of theUS oil and gas business by providing extended use solutions for

depleted oil and gas wells as LT geothermal energy suppliers. A feasi-bility study is fully enabled by the proposed spreadsheet-based deci-sion-making tool. Subsequent pilot scale testing can be executed withvery minor investment by three assumed business partners, the actualcapex portions committed by each partner is specified by the tool afteroptimization for the required IRR using a goal-seek function. An end-user MOU for the pilot stage helps de-risk the business case by ac-cepting a certain service charge/kwh, scaled for a building of 10,000 sqft and its space conditioning solution developed in our case study. Thespreadsheet tool can be used to ensure that the principal partners willmeet their IRR targets, conditional on the reservoir performance in thepilot study will actually confirm that the flux and temperature of thebrine produced by the well meets the required longevity for the laterfull-scale project's duration.

The developed spreadsheet can be used to update inputs for both thetechnical and economic performance targets during the course of theproject. The initial project's aim is to validate whether the target valuescan be delivered by testing installation output capacity and calibrating(and minimizing) the decline rate of the reservoir temperature whileensuring the required flux will be delivered. The spreadsheet decision-making tool developed in this study enables upscaling of the NPV whenthe end-users accept a long-term Service Purchase Agreement (SPA),based on the outcome of the material completion of the pilot's con-struction and validation that performance targets can be met.

The structured approach for both the feasibility study and its asso-ciated investment decisions helps mitigate project uncertainty andthereby reduces risk exposure. The accuracy of the performance fore-cast can be updated as soon as new performance parameters from thegeothermal field and the installations have been obtained, No com-parable tool exists for the application envisioned in this study.

Acknowledgement

An Interdisciplinary Seed Grants for Energy Research was providedto the senior author by Texas A&M Engineering Experiment Station(TEES), Dwight Look College of Engineering, and Texas A &M Kingsville(TAMUK). The Interdisciplinary Seed Grants for Energy Research aim tofoster collaborations among researchers and provides faculty with re-sources to generate preliminary results for future grant submissions.

Nomenclature

sq. ft =square footm3 =cubic metersW =Wattgpm =gallon per minute

Fig. 23. Set of decision-making criteria and targets required for evaluating and adjusting reservoir performance in Pilot Project.

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bbl =barrel°C =degrees Celcius°F =degrees FahrenheitJ =Joulesg =gramK =degrees kelvinρM =specific gravity matrixcM =specific heat matrixA =reservoir aread =reservoir thicknessΦ =porosityρL =specific gravity liquidscL =specific heat liquidsTR =reservoir temperatureTA =ambient temperaturekcal =kilocaloriesREF =Reservoir Efficiency Factort =timeFLF =Wellbore Fluid Heat Loss FactorEQ =energy production rateqL = liquids flow ratehrsopp =hours operating in a day for adsorption chillerhrsstd =hours operating in a day for standard chillercap =capacity of adsorption chillerTonsstd =nameplate refrigeration capacity of standard chillerTonsad =nameplate refrigeration capacity of adsorption chillerhp =horsepowerh =hoursIRR =internal rate of returnNPV =net present valueNPV10 =net present value discounted at 10%FID = final investment decisionAPO =after payoutBPO =before payoutCapex =capital expendituresOpex =operating expenditures

Appendix A. Spreadsheet model use instructions

Prior to opening the spreadsheet, it is necessary to download and install @Risk. There are free trials available as well as significant discounts foruse in academia available from Palisade (http://www.palisade.com/risk/).

Once downloaded, open the Geothermal Econs ‘Control Panel’ tab. The general workflow is top to bottom. First select the area of the countrywhere the project is to take place and enter the approximate square footage to be conditioned. Based on those inputs the sheet will tell you what sizeof HVAC equipment is necessary to cool the space in tons of refrigeration.

Next, click the Calculate Geothermal Energy in Place’. Once open enter numerical parameters in the specified boxes on the left with whateverunits necessary from the drop-down boxes on the right. Once done, click the button for calculate button and a new number will appear in the top greybox of the ‘Original Energy In Place’ table. The green boxes below this number are available as inputs to the user to define required cooling capacityas well as project life and an average usage time per day. The other grey boxes are intermediate calculations as well as a final result indicatingwhether enough geothermal energy is present to run the project.

Now go to the Economic Parameter Distribution Assumptions box and enter the range of values for each variable with green boxes. Thesevariables are explained in detail in Step 1 of Section 4.1.

After that is complete enter all values in the green boxes of the ‘Deal Structure/Operational Inputs’ box. Once all the values are entered, press the‘Structure Deal’ button. If any of the values are changed, it is necessary to press the ‘Reset Structure’ button and then press the ‘Structure Deal’ buttonagain.

Now the simulation needs to be set up, from the @Risk tab, select the ‘Simulation Settings’ option and go to the ‘Macros’ tab (Fig. 24). From here,the By Changing Cell should always be B51, however the Set Cell can be modified depending on which party the user wants to set the return hurdlefor. The default case is a 10% return to the Operating Company. Once that is set and the number of Iterations are defined (usually 1000), the ‘StartSimulation’ button is pressed.

When the simulation is complete, various outputs can be observed via the ‘Browse Results’ button, but the initial one of importance is the cents/kWh required. The values of this distribution can by input in the green box of the Metrics section to explore how the IRR for each party variesdepending on the rate selected for use in the SPA.

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Fig. 24. @Risk Simulation Settings Dialog.

References

[1] Drillinginfo, DI desktop, www.drillinginfo.com, (2017) , Accessed date: 20 June2017.

[2] RRC, Texas Railroad commission applications and permits, http://www.rrc.state.tx.us/oil-gas/applications-and-permits/, (2017) , Accessed date: 22 June 2017.

[3] R. Weijermars, US shale gas production outlook based on well roll-out rate sce-narios, Appl. Energy 124 (2014) 283–297.

[4] R. Weijermars, Barnett at DFW provides lessons on shale gas projects at US airports,Oil Gas J. 111 (8) (2013) 22–27.

[5] Geysers Geothermal Association, 50 Years of development at the Geysers, http://thegga.org/50years-1960.htm/, (2011) , Accessed date: 30 April 2017.

[6] GEA, Annual US & global geothermal power production report, http://geo-energy.org/reports/2016/2016%20Annual%20US%20Global%20Geothermal%20Power%20Production.pdf, (2016) , Accessed date: 1 May 2017.

[7] EIA, US energy information administration electric power monthly, http://www.eia.gov/electricity/monthly/current_year/february2016.pdf, (2016) , Accesseddate: 20 February 2017.

[8] NREL, National renewable energy laboratory geothermal resource potential, http://www.nrel.gov/gis/images/geothermal_resource2009-final.jpg, (2009) , Accesseddate: 21 July 2017.

[9] C.F. Williams, M.J. Reed, R.H.A. Mariner, Review of methods applied by the USgeological Survey in the assessment of identified geothermal resources, USDepartment of the Interior, US Geological Survey (2008) 2008; Open-File ReportNo.:2008-1296:27.

[10] S.D. Zafar, B.L. Cutright, Texas' geothermal resource base: a raster-integrationmethod for estimating in-place geothermal-energy resources using ArcGIS,Geothermics 50 (2014) 148–154.

[11] R. Weijermars, L. Zuo, I. Warren, Modeling reservoir circulation and economicperformance of the neal hot springs geothermal power plant (Oregon, US): an in-tegrated case study of a commercially successful power plant, Geothermics 70(2017) 155–172.

[12] A.P. Barbacki, The use of abandoned oil and gas wells in Poland for recoveringgeothermal heat, Proceedings, World Geothermal Congress, Kyushu - Tohoku,Japan, 2000.

[13] L. Zhang, J. Yuan, H. Liang, K. Li, Energy from abandoned oil and gas reservoirs,Proceedings, Asia Pacific Oil and Gas Conference and Exhibition, Perth, Australia,2008.

[14] A.P. Davis, E.E. Michaelides, Geothermal Power Production from Abandoned OilWells, Energy, 2009, p. 34.

[15] X. Bu, W. Ma, H. Li, Geothermal energy production utilizing abandoned oil and gaswells, Renew. Energy 41 (2012).

[16] E. Soldo, C. ana Alimonti, From an oilfield to a geothermal one: use of a selectionmatrix to choose between two extraction technologies, Proceedings WorldGeothermal Congress 2015; Melbourne, Australia, 19-25 April 2015, 2015.

[17] M. Røksland, T.A. Basmoen, D. Sui, Geothermal energy extraction from abandonedwells. The 8th international conference on applied energy – ICAE2016, EnergyProcedia 105 (2017) 244–249.

[18] R.A. Caulk, I. Tomac, Reuse of abandoned oil and gas wells for geothermal energyproduction, Renew. Energy 112 (2017) 388–397.

[19] T. Sliwa, M.A. Rosen, Z. Jezuit, Use of oil boreholes in the carpathians in geoe-nergetic systems: historical and conceptual review, Res. J. Environ. Sci. 8 (5) (2014)231.

[20] T. Sliwa, A. Gonet, A. Sapinska-Sliwa, D. Knez, Z. Jezuit, Applicability of boreholeR-1 as BHE for heating of a gas well, Proceedings World Geothermal Congress 2015,2015.

[21] J.A. Griggs, Reevaluation of Geopressured Geothermal Aquifers as an EnergyResource, MS Thesis Lousiana State University, 2004.

[22] J.A. Griggs, Reevaluation of geopressured geothermal aquifers as an energy re-source, Proceedings of the 30th Workshop on Geothermal Reservoir Engineering,Stanford University, California, 2005.

[23] L. Johnson, E. Walker, Ormat: Low-temperature Geothermal Power Generation, TheUnited States Department of Energy, Wyoming, USA, 2010.

[24] Y. Wei, F. Wang, B. Ren, Drainage and Production by Using Geothermal in HuabeiOil Region, Huabei Oilfield Production Technology Research Institute, Renqiu,2009.

[25] S. Xin, H. Liang, B. Hu, K. Li, Electrical power generation from low temperature co-produced geothermal resources at Huabei Oilfield, Proceedings, 37th Workshop onGeothermal Reservoir Engineering, Stanford University, Stanford, CA, 2012.

[26] R.J. Erdlac, Geopowering Texas: a Report to the Texas State Energy ConservationOffice on Developing the Geothermal Energy Resource of Texas, Center for Energy& Economic Diversification, 2007 Contract No.:DEFG3605GO85023.Sponsored bythe Department of Energy.

[27] Tester, et al., The Future of Geothermal Energy. Impact of Enhanced GeothermalEnergy Systems (EGS) on the United States in the 21st Century. An Assessment byan MIT-led Interdisciplinary Panel, Idaho National Laboratory, Subcontract, 2006No.: 6300019 of Contract No.: DEAC0705ID14517. Sponsored by the Department ofEnergy.

[28] B.C. Lunis, J. Negus-deWys, M.M. Plum, P.J. Lineau, F.J. Spencer, G.F. Nitschke,The Feasibility of Applying Geopressured-geothermal Resources to Direct Use,Oregon Institute of Technology Geo-Heat Center, 1991 Contract No.:DEAC0771D01570. Sponsored by the Department of Energy.

[29] P. Tidwell, D.B. Burnett, Low Temperature Geothermal Waste-heat-to-power. GPRIReport of Investigation White Paper, (2014).

[30] D. Blackwell, M. Richards, P. Stepp, Texas Geothermal Assessment for the I35Corridor East. Final Report. Southern Methodist University Geothermal Laboratory,(2010) Contract No.: CM709. Sponsored by the Texas State Energy ConservationOffice.

[31] W. Gosnold, Recovery Act: Electrical Power Generation from Low to IntermediateTemperature Resources. Final Technical Report, University of North Dakota, 2017Contract No.:DEEE0002854. Sponsored by the Department of Energy.

[32] EERE, EERE Success Story—doe-funded Project Is First Permanent Facility to Co-produce Electricity from Geothermal Resources at an Oil and Gas Well, (2016)accessed http://energy.gov/eere/success-stories/articles/eere-success-story-doe-funded-project-first-permanent-facility-co , Accessed date: 7 January 2017.

[33] G.L. Dittman, Calculation of Brine Properties, Lawrence Livermore Laboratory,1977 Contract No.: W7405ENG48. Sponsored by the US Energy Research andDevelopment Administration.

[34] B.J. Anderson, Recovery Act: Analysis of Low-temperature Utilization ofGeothermal Resources. Final Technical Report, West Virginia University ResearchCorporation, 2015 Contract No.: DEEE0002745. Sponsored by the Department ofEnergy.

[35] J.S. Gifford, R.C. Grace, CREST Cost of Renewable Energy Spreadsheet Tool: aModel for Developing Cost-based Incentives in the United States. User ManualVersion 4 August 2009 — March 2011 (Updated July 2013). Subcontract ReportNREL/SR-6A20-50374, (2013).

[36] K. Beckers, GEOPHIRES software tool. Retrieved from geothermal energy for theproduction of heat and electricity economically simulated, http://koenraadbeckers.net/geophires/index.php, (2015).

[37] K.F. Beckers, M.Z. Lukawski, B.J. Anderson, M.C. Moore, J.W. Tester, Levelizedcosts of electricity and direct-use heat from Enhanced Geothermal Systems, J.Renew. Sustain. Energy 6 (No. 1) (2014) 013141.

[38] K.F. Beckers, M.Z. Lukawski, T.J. Reber, B.J. Anderson, M.C. Moore, J.W. Tester,Introducing GEOPHIRES V1.0: software package for estimating levelized cost ofelectricity and/or heat from enhanced geothermal systems, Proceedings, Thirty-eighth Workshop on Geothermal Reservoir Engineering, Standford University,

D. Westphal, R. Weijermars Energy Strategy Reviews 22 (2018) 348–364

363

Standford, 2013Retrieved from http://www.geothermal-energy.org/pdf/IGAstandard/SGW/2013/Beckers.pdf.

[39] R. Weijermars, D. Claridge, D. Burnett, M. Pate, S. Noyanaert, W. Yu, L. Zuo,Redeveloping depleted hydrocarbon wells in an enhanced geothermal system (EGS)for a university campus: progress report of a real-asset-based feasibility study,Energy Strategy Reviews 21 (2018) 191–203.

[40] A. Conser, Double dipping: utilizing oil wells or geothermal energy, William MaryEnviron. Law Pol. Rev. 37 (3) (2013) 813–843 article 7.

[41] A.H. Lachenbruch, Surficial thermal regime inside Long Valley caldera, J. Geophys.Res. 80 (1975).

[42] S.K. Garg, J. Combs, Appropriate use of USGS volumetric "heat in place" methodand Monte Carlo Calculations, Proceedings, Thirty-fourth Workshop on GeothermalReservoir Engineering Stanford University, Stanford, California, February 1-3, 2010SGP-TR-188, 2010.

[43] L. Rybach, Classification of geothermal resources by potential, Geoth. Energ. Sci. 3(2015) 13–17, https://doi.org/10.5194/gtes-3-13-2015 2015 www.geoth-energ-sci.net/3/13/2015/.

[44] UNECE, Specifications for the Application of the United Nations FrameworkClassification for Fossil Energy and Mineral Reserves and Resources 2009 (UNFC-2009) to Geothermal Energy Resources. United Nations Economic Commission forEurope Expert Group on Resource Classification. Draft Document Prepared by theGeothermal Working Group, (2016) Version 30 May 2016 https://www.unece.org/fileadmin/DAM/energy/se/pdfs/UNFC/UNFC2009_publcom.geoth.2016/Geothermal.Specs_for.public.comment.pdf.

[45] P. Franz, M. Neville-Lamb, L. Azwar, J. Quinao, Calculation of geothermal storedheat from a numerical model for reserve estimation, Proceedings World GeothermalCongress 2015; Melbourne, Australia, 19-25 April 2015, 2015.

[46] Material property data. MatWeb. Calcium carbonate, calcite (CaCO3), http://www.matweb.com/search/datasheet_print.aspx?matguid=bea4bfa9c8bd462093d50da5eebe78ac, (2017) , Accessed date: 24 June 2017.

[47] US Geological Survey, USGS Austin Chalk, https://mrdata.usgs.gov/geology/state/sgmc-unit.php?unit=TXKau%3B0, (2017) , Accessed date: 24 June 2017.

[48] L. Zuo, R. Weijermars, Scoping model of geothermal heat extraction potential forabandoned hydrocarbon wells, Geophys. J. Int. (2018) in revision.

[49] S. Tekin, S. Akin, Estimation of the formation temperature from the inlet and outletmud temperatures while drilling geothermal formations, Proceedings of the36thWorkshop on Geothermal Reservoir Engineering; 2011 Jan 21 – Feb 2, StanfordUniversity, California, 2011.

[50] L.R. Raymond, Temperature distribution in a circulating drilling fluid, J. Petrol.Technol. 21 (2) (1969) 333–341.

[51] Bryair, Adsorption chiller tech data, http://www.bryair.com/pdf/Adsorption_Chiller_C-Frame_tech_data.pdf, (2017) , Accessed date: 4 March 2017.

[52] EcoMax Chillers. (2–17) EcoMax Chillers Representative Wes Livingston, http://www.eco-maxchillers.com/;[accessed 23.06.2017].

[53] EnergyDesignResources, Design brief - chiller plant efficiency, https://energydesignresources.com/media/1681/edr_designbriefs_chillerplant.pdf, (2017), Accessed date: 23 June 2017.

[54] Ohio's Electric Cooperative, Questline ask an expert - estimating kilowatt demandfrom air conditioning tons, http://members.questline.com/Article.aspx?articleID=7018&accountID=9&nl=14883, (2017) , Accessed date: 23 June 2017.

[55] AC4Life, Air conditioning sizing calculator, 2016 http://www.acdirect.com/ac-package-unit-learning-center-ac-sizing-calculator, (2016) , Accessed date: 22 June2017.

[56] Google Unit Converter,www.google.com; [accessed 20.02.2017].

D. Westphal, R. Weijermars Energy Strategy Reviews 22 (2018) 348–364

364